• Online, Self-Paced

Predictive analytics involves widely accepted tools and techniques that enable organizations to make informed decisions regarding potential future events. Explore how correlation and regression are employed in predictive analytics.

Learning Objectives

Correlation and Regression

  • start the course
  • identify key features of correlation
  • recognize how correlation is used in predictive analytics
  • recognize when correlation indicates causation and when it doesn't
  • distinguish between statistical versus practical significance
  • recognize the role of regression in predictive analytics
  • identify how the predictive power of a model can be assessed using the r-squared metric
  • recognize key features of logistic regression

Practice: Applying Statistical Approaches

  • identify the correct regression technique to use in a given situation

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • All-Source Analysis
  • Data Administration
  • Systems Analysis

Specialty Areas have been removed from the NICE Framework. With the recent release of the new NICE Framework data, updates to courses are underway. Until this course can be updated, this historical information is provided to give better context as to how it can help you with your cybersecurity goals.

Feedback

If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.